Edtech.com's Summary

The Pennsylvania State University is hiring an Undergraduate Researcher in Multi-Agent Reinforcement Learning. This part-time role involves conducting research on multi-agent deep reinforcement learning by designing novel algorithms and architectures, running computational experiments in benchmark environments, and preparing reports on the findings.

Highlights

Conduct research in multi-agent deep reinforcement learning, including algorithm design and computational experiments.
Design novel algorithms and architectures for multi-agent systems.
Perform experiments using multi-agent benchmark environments such as MPE and SMAC.
Compile and report research results effectively.
Required knowledge of deep reinforcement learning theory and state-of-the-art multi-agent algorithms, including value-decomposition and policy-based methods.
Hands-on experience with deep learning frameworks, specifically PyTorch.
Starting compensation rate is $20 per hour.
Employment requires successful completion of background checks per University policies.
Position is part-time and located at Penn State University Park.
Equal opportunity employer committed to diversity, equity, and inclusion.

College of IST- Undergraduate Researcher in Multi-Agent Reinforcement Learning Full Description

APPLICATION INSTRUCTIONS:

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CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
If you are NOT a current employee or student, please click "Apply" and complete the application process for external applicants.

Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.

JOB DESCRIPTION AND POSITION REQUIREMENTS

The College of IST is seeking applicants for part-time job of Undergraduate Researcher in Multi-Agent Reinforcement Learning.

Job duties to include:

Conduct research on multi-agent deep reinforcement learning, including designing novel algorithms and architectures, conducting computational experiments in benchmark environments, and compiling results into reports.

Requirements, qualifications, and/or competencies:

familiarity with the theory of deep reinforcement learning
familiarity with state-of-the-art multi-agent reinforcement learning algorithms, including both value-decomposition and policy-based methods
experience with deep learning, including hands-on experience with PyTorch
experience with conducting experiments in multi-agent benchmark environments, including MPE and SMAC

Compensation:

The starting rate for this job is $20.

BACKGROUND CHECKS/CLEARANCES
Employment with the University will require successful completion of background check(s) in accordance with University policies.

CAMPUS SECURITY CRIME STATISTICS

Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.

EEO IS THE LAW

Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.

Penn State is committed to and accountable for advancing equity, respect, and belonging. We embrace individual uniqueness, as well as a culture of belonging that supports equity initiatives, leverages the educational and institutional benefits of inclusion in society, and provides opportunities for engagement intended to help all members of the community thrive. We value belonging as a core strength and an essential element of the university's teaching, research, and service mission.

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Original Job Description